Recently, multi-fingered robotic hands having hands shaped like human hands have been developed. The human hand posture estimating technology is available as a technology needed at the time of driving hands of such a multi-fingered robotic hand or a technology needed at the time of inputting information into a computer through gestures or sign language motions. Conventionally, various technologies of estimating human hand posture have been proposed (see, for example, Patent Literatures 1 and 2, and Non-patent Literatures 1 and 2).
Patent Literatures 1 and 2, and Non-patent Literature 1 propose a human hand posture estimating method that saves sets of the amount of low-order image characteristics of hand images and joint angle data in a database beforehand, and collates an unknown hand image input from a camera with data contained in the database to search for similar images.
Non-patent Literature 2 proposes a scheme of searching for similar images based on positional information on finger nails in a hand image in addition to the image characteristic amount used in the human hand posture estimating method proposed in Patent Literatures 1 and 2, and Non-patent Literature 1.
To improve the accuracy of estimating human hand postures in the aforementioned human hand posture estimating technology, the scale of the database for hand images should be made larger. When the scale of the database becomes larger, however, retrieval takes time. To address this problem, Patent Literature 2 and Non-patent Literature 1 further propose a scheme of retrieving human hand postures similar to an unknown input image from a large-scale database at a high speed.
The human hand posture estimating method proposed in Patent Literature 2 and Non-patent Literature 1 will be described specifically referring to FIG. 41, FIGS. 42A and 42B, and FIGS. 43A and 43B. FIG. 41 is a schematic structural diagram of a database, FIGS. 42A and 42B, and FIGS. 43A and 43B are diagrams illustrating retrieval procedures for unknown sequential images input. For the sake of simplicity, the database is exemplified in two layers.
First, a multi-layer database as shown in FIG. 41 is created. It is to be noted however that at this time, a multi-layer database is created using self-organizing maps involving self-reproduction and self-quenching in such a way that similar human hand posture images are arranged close to one another and the quantities of data sets belonging to individual classes become approximately even.
Next, when a first unknown hand image (first image) is input, all the classes in the multi-layer database will be searched with respect to the first image as shown in FIG. 42A (search region 60 encircled by the dashed line in FIG. 42A). Then, joint angle data of a finger corresponding to the amount of characteristics most similar to the amount of characteristics of the first image in the target is output (arrow A1 in FIG. 42A).
Next, when an unknown hand image (second image) at the next time is input, as shown in FIG. 42B, classes in the vicinity of the class to which image data output in the search at the previous time (e.g., both adjacent classes) becomes the search target (search region 61 encircled by the dashed line in FIG. 42B) for the second image. When similar images are retrieved in the same class again in this search as shown in FIG. 42B (arrow A2 in FIG. 42B), retrieval is performed in the same search area 61 as shown in FIG. 42B for a hand image (third image) at the next time, as shown in FIG. 43A.
Then, suppose that in the retrieval of the third image, as shown in FIG. 43A, for example, similar images are retrieved in a class different from the class where the second image is detected (class adjacent on the right to the second image detecting class) (arrow A3 in FIG. 43A). In this case, search for a hand image (fourth image) at the next time is carried out with the search region (search class) shifted in such a way that the class where the third image is retrieved comes to the center of the search region (search region 62 encircled by the dashed line in FIG. 43B).
According to the technology proposed in Patent Literature 2 and Non-patent Literature 1, the search space can be narrowed and the processing time can be shortened by making data in the vicinity of the result of retrieval at one previous time the search target as mentioned above.